Time Series Analysis

Time Series Analysis is a statistical technique used to analyze and model time-based data. It is used in various fields such as finance, economics, and engineering to analyze patterns and trends in data over time. The goal of time series analysis is to identify the underlying patterns, trends, and seasonality in the data, and to use this information to make informed predictions about future values.

( Image credit: Autoregressive CNNs for Asynchronous Time Series )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1411–1420 of 6748 papers

Title	Date	Tasks	Status
Modeling Nonlinear Dynamics in Continuous Time with Inductive Biases on Decay Rates and/or Frequencies	Dec 26, 2022	Time SeriesTime Series Analysis	—Unverified
Modeling Time-Series and Spatial Data for Recommendations and Other Applications	Dec 25, 2022	Activity PredictionPoint Processes	—Unverified
Streaming Traffic Flow Prediction Based on Continuous Reinforcement Learning	Dec 24, 2022	reinforcement-learningReinforcement Learning	—Unverified
Simple Yet Surprisingly Effective Training Strategies for LSTMs in Sensor-Based Human Activity Recognition	Dec 23, 2022	Activity RecognitionHuman Activity Recognition	—Unverified
Security and Interpretability in Automotive Systems	Dec 23, 2022	Decision MakingTime Series Analysis	—Unverified
Few-shot human motion prediction for heterogeneous sensors	Dec 22, 2022	Few-Shot LearningHuman motion prediction	CodeCode Available
Machine Learning with Probabilistic Law Discovery: A Concise Introduction	Dec 22, 2022	Anomaly DetectionTime Series	—Unverified
Is it worth it? Comparing six deep and classical methods for unsupervised anomaly detection in time series	Dec 21, 2022	Anomaly DetectionTime Series	CodeCode Available
Temporal Disaggregation of the Cumulative Grass Growth	Dec 21, 2022	Time SeriesTime Series Analysis	—Unverified
A Query-Response Causal Analysis of Reaction Events in Biochemical Reaction Networks	Dec 21, 2022	Time SeriesTime Series Analysis	—Unverified

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All datasets PhysioNet Challenge 2012 Speech Commands Ventilator Pressure Prediction

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	naive classifier	F1	87.47	—	Unverified
2	GRU-D - APC (n = 1)	F1	27.3	—	Unverified
3	GRU-APC (n = 1)	F1	25.7	—	Unverified
4	GRU-D	F1	22.5	—	Unverified
5	GRU	F1	22.3	—	Unverified
6	GRU-Simple	F1	22.2	—	Unverified
7	GRU-Mean	F1	22.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SepTr	% Test Accuracy	98.51	—	Unverified
2	ViT	% Test Accuracy	98.11	—	Unverified
3	FlexTCN-4	% Test Accuracy	97.73	—	Unverified
4	MatchboxNet	% Test Accuracy	97.4	—	Unverified
5	CKCNN (100k)	% Test Accuracy	95.27	—	Unverified
6	FlexTCN-6	% Test Accuracy (Raw Data)	91.73	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResBiLSTM	MAE	0.13	—	Unverified